This function has been made defunct and replaced.
Use as.character.corpus()
to turn a corpus into a simple named character
vector.
Use corpus_group()
instead of texts(x, groups = ...)
to aggregate texts
by a grouping variable.
Use [<-
instead of texts()<-
for replacing texts in a corpus object.
texts(x, groups = NULL, spacer = " ")
texts(x) <- value
a corpus
grouping variable for sampling, equal in length to the number
of documents. This will be evaluated in the docvars data.frame, so that
docvars may be referred to by name without quoting. This also changes
previous behaviours for groups
. See news(Version >= "3.0", package = "quanteda")
for details.
when concatenating texts by using groups
, this will be the
spacing added between texts. (Default is two spaces.)
character vector of the new texts
For texts
, a character vector of the texts in the corpus.
For texts <-
, the corpus with the updated texts.
for texts <-
, a corpus with the texts replaced by value
Get or replace the texts in a corpus, with grouping options.
Works for plain character vectors too, if groups
is a factor.
The groups
will be used for concatenating the texts based on shared
values of groups
, without any specified order of aggregation.
You are strongly encouraged as a good practice of text analysis
workflow not to modify the substance of the texts in a corpus.
Rather, this sort of processing is better performed through downstream
operations. For instance, do not lowercase the texts in a corpus, or you
will never be able to recover the original case. Rather, apply
tokens_tolower()
after applying tokens()
to a
corpus, or use the option tolower = TRUE
in dfm()
.